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How AI Is Revolutionizing Pricing on Amazon and Walmart
SUMMARY
Discover how AI-powered pricing is revolutionizing e-marketplaces, enabling dynamic, real-time strategies to maximize profitability and outpace competitors.
Rachel Horner
Rachel Horner serves as a Content Marketing Writer for Feedvisor. She has extensive experience in writing for diverse B2B brands, particularly in the tech industry, and is dedicated to fostering meaningful brand-audience connections.
AI has transformed nearly every aspect of the Amazon e-marketplace, from packaging and shipping to advertising and beyond. Pricing, in particular, has long been at the forefront of AI’s impact, automating processes and enabling brands to respond quickly to market changes.
Prior to AI-driven pricing, early rule-based pricing was the standard, relying on rigid, pre-set rules that, while fast, couldn’t adapt to changing business goals. As the marketplace evolved, their lack of flexibility, sophistication, and adaptability became a limitation. AI has not only reshaped pricing but continues to push its boundaries, transforming how brands and sellers operate and compete.
Below, we’ll dive into the various capabilities of AI-powered pricing that are transforming the landscape, helping you understand why AI technology should play a key role in your pricing strategy.
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Dynamic Pricing – The Key to Keeping Pace With a Changing Market
Price doesn’t exist in a vacuum—today’s market involves a wide range of dynamic factors that can be difficult to capture manually.
Pricing optimization powered by AI allows brands to adapt quickly to these fluctuations, even enabling real-time price adjustments. As AI uses reinforcement learning—learning from trial and error to improve decisions—it also takes into account other factors that affect pricing. This includes analyzing various data points that impact demand, such as:
- Price changes
- Competitor pricing
- Sales volume
- Traffic
- Stock levels
- Ad spend
- Seasonality
This approach works year-round, but it’s especially effective for seasonal events. Dynamic pricing adjusts in near real-time to market shifts and demand fluctuations, enabling you to capitalize on seasonality, shopper trends, and market changes. This helps to maximize profits during busy seasons and focus on revenue during slower months.
Traditional rule-based repricers, on the other hand, rely on manual input to adjust for changes in demand or competition. This reliance on human intervention makes them reactive, slowing down the process of implementing changes.
Adapts to Business Objectives
Historically, pricing strategies were bound by rigid rules, preventing them from adapting to evolving business objectives. This lack of flexibility made it challenging to align pricing with key goals like maximizing profitability or capturing market share.
AI changes this by enabling pricing optimization technology to adapt to specific business objectives, such as:
- Profit optimization: Maximizing margins while remaining competitive.
- Driving sales: Adjusting prices to increase conversions and volume.
- Winning the Buy Box: Strategically adjusting prices to improve your chances of securing the coveted Buy Box.
Reinforcement learning—an advanced technique where algorithms continuously learn from past outcomes and feedback— plays a key role here to fine-tune pricing strategies in real time. By analyzing a vast amount of data, including market shifts, competitor behavior, and customer responses, AI-driven pricing optimization technologies can adjust pricing to align with specific business objectives. This adaptability allows businesses to meet key KPIs while staying agile in a dynamic market, ensuring pricing decisions are always in sync with overarching goals.
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Real-Time Optimization Means Pricing is no Longer About the Short-Term–It’s a Long-Term Strategy
Many people equate price optimization with the lowest price, but the best price isn’t always the cheapest. Too often, businesses fall into price wars, slashing prices and risking profit loss. But with true price optimization, price wars become child’s play.
Unlike basic solutions that simply react to competitors—pushing prices down at the cost of profits or triggering price wars—smarter options constantly search for the optimal price. They make real-time adjustments based on multiple factors, aiming not for the lowest price, but the one that maximizes sales without sacrificing margins, enabling merchants to stay competitive without compromising profitability.
What’s more, AI has enabled pricing optimization technology to grow alongside your business. Unlike rule-based pricing, which follows static, pre-determined rules and struggles to adapt to market changes, AI-powered pricing learns and evolves, continuously refining strategies to stay aligned with shifting dynamics.
Integrated With Real-Time Inventory Data
Managing stock levels manually in Amazon’s dynamic marketplace is a challenge, especially with fluctuating prices and shifting consumer demand. Traditional, rule-based pricing technology, relying on static rules, can’t adapt to these changes, making it difficult to keep up with inventory fluctuations and avoid fees.
Today’s pricing technology integrates real-time inventory data, feeding it into AI algorithms to fine-tune price adjustments and prevent inventory issues that can incur costly FBA fees. It’s all possible by merging smart algorithms, competitive signals, and real-time inventory insights together to adjust prices in real time, optimizing inventory velocity and maintaining balanced stock levels.
Omnichannel Becomes Multichannel
Being present on both Amazon and Walmart is crucial for your brand, but optimizing on both platforms can be challenging. Each requires its own strategy, and failing to manage them properly can lead to risks like Buy Box suppression. AI streamlines multi-channel optimization by integrating real-time data across platforms, handling the complex adjustments for each channel, and freeing up your time to focus on growth.
Imagine a brand notices a competitor listing their product at a lower price on Amazon, causing their Buy Box to be suppressed and sales to drop. AI can help by continuously monitoring competitor prices across multiple channels. When it detects a lower price, the AI adjusts the seller’s price in real time to stay competitive. At the same time, it analyzes sales data and competitor pricing trends to ensure the seller’s prices remain within an acceptable range relative to MSRP to prevent Buy Box suppression.
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Final Thoughts
Now that you’ve explored the game-changing capabilities of AI-powered pricing, it’s time to reflect: How does your current pricing strategy measure up? Are you leveraging the latest AI-driven technology, or are you still relying on outdated rule-based methods that could leave you vulnerable to more advanced competitors?
To unlock the full potential of AI and see how it can transform your business, take advantage of Feedvisor’s free 14-day trial. Experience firsthand how our cutting-edge AI algorithmic technology can optimize your Amazon strategy and give you the competitive edge you need to succeed.
